title: Adapting parcellation schemes to study fetal brain connectivity in serial imaging studies.
abstract: A crucial step in studying brain connectivity is the definition of the Regions Of Interest (ROI's) which are considered as nodes of a network graph. These ROI's identified in structural imaging reflect consistent functional regions in the anatomies being compared. However in serial studies of the developing fetal brain such functional and associated structural markers are not consistently present over time. In this study we adapt two non-atlas based parcellation schemes to study the development of connectivity networks of a fetal monkey brain using Diffusion Weighted Imaging techniques. Results demonstrate that the fetal brain network exhibits small-world characteristics and a pattern of increased cluster coefficients and decreased global efficiency. These findings may provide a route to creating a new biomarker for healthy fetal brain development.
authors.forename: Xi
authors.initials: X
authors.lastname: Cheng
authors.forename: Jakob
authors.initials: J
authors.lastname: Wilm
authors.forename: Sharmishtaa
authors.initials: S
authors.lastname: Seshamani
authors.forename: Mads
authors.initials: M
authors.lastname: Fogtmann
authors.forename: Christopher
authors.initials: C
authors.lastname: Kroenke
authors.forename: Colin
authors.initials: C
authors.lastname: Studholme
mesh_terms: D000465:Algorithms; D000818:Animals; D015415:Biomarkers / Q000032:analysis; D001921:Brain / Q000000981:diagnostic imaging*; D001931:Brain Mapping; D038524:Diffusion Magnetic Resonance Imaging; D005333:Fetus; D005865:Gestational Age; D000882:Haplorhini; D011859:Radiography; D012815:Signal Processing, Computer-Assisted
chemical_list: D015415:Biomarkers